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Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at www.cambridge.org/9781107607590, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

Features several complete data analysis case studies using real data from great scientific experiments

Boxed text contains worked examples and computer codes to help further understanding of the concepts covered in the main text

Presents a self-contained introduction to statistical computing using the freely available R language

Reviews & endorsements

'… provides innovative and intelligent comments and connecting elements, as well as data analysis and interpretation … [it] extends to fundamental and known issues, which are offered from an understandable point of view.'
Nikolaos E. Myridis, Contemporary Physics

Resources for

Scientific Inference

Simon Vaughan

General Resources

Lecturer Resources

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Author

Simon Vaughan, University of LeicesterSimon Vaughan is a Reader in the Department of Physics and Astronomy, University of Leicester, where he has developed and runs a highly regarded course for final year physics students on the subject of statistics and data analysis.

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